Ringraziamo il personale presso i Laboratori Anatomia Patologica del Principe Reale Alfred e Ospedali rimpatrio Concord per la raccolta di campioni freschi di CRC e normale mucosa intestinale. Il lavoro è stato finanziato da un Istituto di Grant Cancro New South Wales Programma traslazionale.

<img src="/files/ftp_upload/3322/3322fig1.jpg" alt="Figura 1" /> Figura 1. Flusso di lavoro per la preparazione di una sospensione di cellule vive da un campione chirurgico di CRC. 1. Disaggregazione del campione clinico Tutti i campioni sono stati raccolti dal Principe Reale Alfred Hospital (Camperdown, NSW, Australia) e l&#39;Ospedale rimpatrio Concord (Concord West, NSW, Australia) con il consenso informato ai sensi del protocollo n. X08-164. <ol><li> Raccogliere fresca cancro del colon-retto (CRC) o campioni adenoma, e normale mucosa intestinale di almeno 10 cm dal tumore. Conservare i campioni a pH salina bilanciata di Hank soluzione 7.3 (HBSS) a 4 ° C per un massimo di 12 ore dopo la resezione. </li><li> Seguire le norme di sicurezza per gli agenti patogeni umani, processo di tutti i campioni clinici in un armadio di sicurezza biologica di classe II. Sezionare i campioni in 2 cubi mm in una capsula di Petri con due lame di bisturi. </li><li> Incubare tumore e tessuto normale in separato tubi Eppendorf con occasionali miscelazione dolce per 60 minuti a 37 ° C con un uguale volume di RPMI 1640 medium contenente il 2% (v / v) collagenasi tipo 4 (Worthington, Lakewood, NJ, USA) e 0,1 % (w / v) deossiribonucleasi ho da pancrease bovina (DNAsi I; Sigma-Aldrich). </li><li> Forza semi-digerito tessuto attraverso un colino fine rete metallica con un pistone di una siringa da 10 ml; lavare le cellule attraverso con HBSS. </li><li> Passare con conseguente sospensione cellulare attraverso 200 micron e 50 filtri Filcon micron (BD Biosciences) per rimuovere aggregati cellulari. La maggior parte degli aggregati di DNA, muco e cellule vengono rimosse in questa serie di filtrazioni. </li><li> Centrifugare sospensioni cellulari a 400 xg a 20 ° per 5 minuti. </li><li> Pellet cellulari risospendere in FCS inattivato al calore contenente il 10% dimetilsolfossido (DMSO), congelare lentamente in cryovials e conservare a -80 °. Il processo di congelamento tende a ridurre il muco nel campione e lisa i globuli rossi. </li></ol> 2. Preparazione del campione per la cattura delle cellule <ol><li> Scongelare i campioni rapidamente in un bagno d&#39;acqua a 37 ° e risospendere le cellule in 10 ml di HBSS per lavare il DMSO. </li><li> Centrifugare sospensioni cellulari a 410 xg a 20 ° per 5 minuti. </li><li> Decantare il supernatante e risospendere il pellet cellulare in 500 ml di HBSS. </li><li> Trattare il campione con 0,1% (w / v) DNAsi I per 20 minuti a temperatura ambiente. </li><li> Miscelare 10 ml di ciascuna sospensione cellulare con un uguale volume di trypan blu e carico 10 microlitri della miscela in un emocitometro. Utilizzando un microscopio ottico a 100 volte ingrandimento, conta cellule vitali, che appaiono chiari a causa dell&#39;esclusione trypan blu, mentre le cellule morte raccogliere la tintura. Un minimo di 4 x 10 6 cellule vitali è necessario per catturare cella del microarray. </li><li> Dopo il trattamento DNAsi, risospendere la sospensione cellulare in 10 ml HBSS e centrifugare a 410 xg a 20 ° per 5 minuti. </li><li> Decantare il sopranatante e risospendere pellet cellulare in RPMI 1640 ad un volume finale di 200 ul. </li></ol> 3. Anticorpo microarray di cattura delle cellule <ol><li> Inumidire il microarray DotScan anticorpi immergendo la sezione nitrocellulosa in tampone fosfato (PBS) per circa 20 s. Asciugare con cura i bordi di vetro del microarray con Kimwipes piegato, evitando di toccare la sezione nitrocellulosa. </li><li> Aggiungere acqua al vassoio di incubazione microarray di fornire una camera umida. Posizionare il microarray nella camera e pipetta sospensione di cellule in RPMI 1640 sulla sezione nitrocellulosa umido. Pipetta gocce su ogni angolo della nitrocellulosa per assicurare un&#39;equilibrata ripartizione delle cellule. </li><li> Incubare il microarray a 37 ° C per 1 h. L&#39;incubazione permette alle cellule di stabilirsi e di entrare in contatto con gli anticorpi sul microarray. Cellule che esprimono antigeni di superficie corrispondente agli anticorpi atterrano sul verrà catturata. </li><li> Dopo l&#39;incubazione, immergere il microarray delicatamente e verticalmente in tre vasche contenenti almeno 15 ml di PBS per lavare le cellule non legato (20 s per ogni lavaggio). </li><li> Preparare 3,7% (w / v) di formaldeide in PBS per fissare le cellule e di anticorpi cross-linking. Delicatamente pipetta circa 1 ml per coprire la sezione nitrocellulosa del microarray. Incubare per 20 minuti a temperatura ambiente. </li><li> Prossimo tuffo microarray in 3 cambi di PBS (15 ml, 30 s ciascuno) per lavare formaldeide in eccesso. </li><li> Pulire i bordi e il retro del vetrino con Kimwipes e la scansione del microarray utilizzando il tempo DotScan scanner, la sezione di nitrocellulosa è umida. La scansione ottica fornisce il pattern di espressione dell&#39;antigene di una popolazione di cellule miste ad esempio cellule di CRC, leucociti ed altre cellule stromali del tumore. </li></ol> 4. Fluorescenza multiplexing <ol><li> Rimuovere il microarray dallo scanner e applicare 200 l di tampone di bloccaggio (2% w / v BSA, 2% di siero umano AB siero, PBS, pH 7,3). Incubare nel vassoio microarray a temperatura ambiente per 20 min. </li><li> Preparare il multiplexing soluzione in una provetta Eppendorf coperto con un foglio di alluminio: 20 l ficoeritrina-anti-CD3 (Beckman Coulter, Gladesville, NSW, Australia, # IM12824; 1/7.5 diluizione finale), 10 L Alexa Fluor 647-anti-EpCAM (Biolegend, San Diego, CA, USA; 1 / 15 di diluizione), 2 ml di inattivato al calore umano siero AB (Sigma-Aldrich, Castle Hill, NSW, Australia) e 118 ml di tampone di bloccaggio. </li><li> Drenare l&#39;eccesso tampone di bloccaggio dal microarray e pipetta la soluzione multiplexing sulla sezione nitrocellulosa, diffondendo uniformemente. Incubare per 30 minuti al buio a temperatura ambiente. </li><li> Immergere il microarray verticalmente in tre depressioni di 15 ml PBS fresco; (30 s ciascuno). </li><li> Lasciate che i microarray asciugare al buio e conservare a 4 ° C in una scatola di diapositive. I microarray possono essere conservati al buio per un massimo di 3 mesi senza perdita di fluorescenza. </li><li> Eseguire la scansione del microarray a secco utilizzando un tifone FLA 9000 scanner (GE Healthcare, Rydalmere, NSW, Australia) con risoluzione impostata a 50 (532 nm laser, 580 BP30 emissione filtro per PE. Laser 633 nm e 670 BP30 emissione filtro per Alexa 647). I microarray sono acquisiti con il lato nitrocellulosa rivolto verso il basso sul vassoio di vetro dello scanner. </li><li> Salvare le immagini come file TIFF fluorescente e utilizzando dimensioni di Photoshop l&#39;immagine a 17 x 25 cm e la risoluzione a 72 pixel / cm. Importa l&#39;immagine nel software di analisi DotScan per analizzare l&#39;intensità di punti. </li><li> Il DotReader cattura una immagine digitale del modello di punti vincolanti e quantifica la densità di cellule vincolanti su ogni punto di anticorpi a livello grigiore 8 bit (1-256 U). Occasionali legame non specifico controllo isotipico è stato sottratto dai valori vincolanti per gli anticorpi di isotipi di immunoglobuline corrispondente. Intensità di fluorescenza punto per ogni microarray sono stati normalizzati contro i più brillanti punto fissato a 100% di intensità. Segnale / punto di forza è stato registrato in un file. Xml (dati grezzi) o rappresentato come un grafico a barre in un file. Pdf (relazione finale) </li><li> Microarray heatsmaps e clustering gerarchico sono stati condotti utilizzando MultiExperiment Viewer (MeV) versione 4.4 dal Microarray TM4 Software Suite ( <a href="http://www.tm4.org/mev.html">http://www.tm4.org/mev.html</a> ). Clustering gerarchico è stata effettuata su dati di base-impostato con MeV con l&#39;analisi di linkage completo. Distanza euclidea è stata utilizzata per la misura di similarità. Il 2-code di Student t-test con varianza pari è stato utilizzato per determinare la significatività statistica dei risultati. </li></ol> 5. Rappresentante dei risultati: I risultati del microarray DotScan dovrebbe mostrare modelli di cellulare coerente legame tra gli array duplicato. Forte allineamento punti vincolanti (CD44/CD29) consente una griglia da posizionare sopra l&#39;area vasta. La Figura 2 mostra un esempio di cattura delle cellule ottimale e multiplexing. La figura 3 mostra alcuni problemi comuni riscontrati durante la cattura delle cellule e le possibili soluzioni. I risultati delle cellule microarray vincolante può essere quantificata misurando intensità puntino espresso su una scala di grigio che vanno da 1 a 256. Figura 4 mostra i dati numerici da 58 campioni chirurgici CRC, colorati con carcinomi Alexa 647 anticorpi, come heatmap con il clustering gerarchico. Anche se il numero di campioni è limitato, CRC della stessa fase tendono a raggrupparsi nello stesso gruppo. <img src="/files/ftp_upload/3322/3322fig2.jpg" alt="Figura 2" /> Figura 2. Modello cellulare vincolante del clinico tumore del colon-retto (Australian Clinic-patologico di sosta, ACP stadio B1). (A) DotScan chiave anticorpi che mostrano le posizioni di anticorpi per la metà sinistra del microarray duplicato (descritto). La parte superiore contiene l&#39;originale 82 anticorpi del microarray leucemia DotScan. Un ulteriore 40 anticorpi, corrispondenti a specifici antigeni di superficie trovato per essere up-regolata in letteratura, sono stati aggiunti come microarray un CRC &#39;satellite&#39;. La sezione inferiore è costituito da anticorpi isotipo di controllo (b) immagine ottico di cellule CRC legame alla microarray. (C) CD3 immagine a fluorescenza che mostra T-cellule. (D) EpCAM fluorescenza immagine che mostra cellule CRC. <img src="/files/ftp_upload/3322/3322fig3.jpg" alt="Figura 3" /> Figura 3. Esempi di poveri risultati DotScan e le possibili soluzioni. (A) cella di bassa vincolante; soluzione: assicurarsi che almeno 4x106 cellule vitali sono sulla matrice (b) cellule di controllo Isotipo vincolanti e non vincolanti specifici; soluzione: aggiungere inattivato al calore umano siero AB a campione prima di incubazione su microarray per minimizzare isotipo di controllo vincolanti. Occasionalmente, una piccola quantità di legame non specifico di cellule per la nitrocellulosa si verifica con i campioni CRC e non influenzano significativamente i risultati. (C) nitrocellulosa essiccazione durante l&#39;incubazione; soluzione: garantire campione copre l&#39;intera sezione nitrocellulosa e microarray è incubata su una superficie piana. (D) manufatti ad alta priorità bassa; soluzione: garantire lamicroarray è accuratamente lavata dopo l&#39;incubazione. <img src="/files/ftp_upload/3322/3322fig4.jpg" alt="Figura 4" /> Figura 4. Software di analisi DotScan generato grafici a barre che rappresentano le densità di cellule vincolante per grigiore una scala da 1 a 256. Numeri sull&#39;asse riferiscono agli antigeni CD. Altre abbreviazioni sono TCR, delle cellule T del recettore; κ, λ, catene leggere delle immunoglobuline, sig, immunoglobuline di superficie, DCC, cancellati nella proteina del cancro del colon-retto; EGFR, epidermal growth factor receptor, FAP, l&#39;attivazione delle proteine ​​dei fibroblasti; HLA-A, B, C HLA-DR, leucocitario umano antigeni DR e A, B, C rispettivamente, MICA, MHC di classe I della catena proteina correlata A; MMP-14, metallopeptidase matrice 14; PIGR, recettore delle immunoglobuline polimeriche; TSP-1, trombospondina-1; MabThera, umanizzato anti-CD20. <a href="http://www.jove.com/files/ftp_upload/3322/3322fig4large.jpg">Clicca qui per vedere l&#39;immagine ingrandita</a> .

<ol>
	<li>Steinert, R., Buschmann, T., vander Linden, M., Fels, L. M., Lippert, H., Reymond, M. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+role+of+proteomics+in+the+diagnosis+and+outcome+prediction+in+colorectal+cancer.">The role of proteomics in the diagnosis and outcome prediction in colorectal cancer.</a> Technol. Cancer. Res. Treat. 1, 297 (2002).</li><li>Eifel, P., Axelson, J. A., Costa, J., Crowley, J., Curran, W. J., Deshler, A., Fulton, S., Hendricks, C. B., Kemeny, M., Kornblith, A. B., Louis, T. A., Markman, M., Mayer, R., Roter, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=National+Institutes+of+Health+Consensus+Development+Conference+Statement:+adjuvant+therapy+for+breast+cancer.">National Institutes of Health Consensus Development Conference Statement: adjuvant therapy for breast cancer.</a> J. Natl. Canc. Inst. 93, 979 (2001).</li><li>Swerdlow, S. H., Campo, E., Harris, H. L., Jaffe, E. S., Pileri, S. A., Stein, H., Thiele, J., Vardiman, J. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=WHO+classification+of+tumour+of+haematopoietic+and+lymphoid+tissues.">WHO classification of tumour of haematopoietic and lymphoid tissues.</a> IARC WHO Classification of Tumours. 2, (2008).</li><li>Xiao, G. G., Recker, R. R., Deng, H. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Recent+advances+in+proteomics+and+cancer+biomarker+discovery.">Recent advances in proteomics and cancer biomarker discovery.</a> Clin. Med. Oncol. , (2008).</li><li>Belov, L., Mulligan, S. P., Barber, N., Woolfson, A., Scott, M., Stoner, K., Chrisp, J. S., Sewell, W. A., Bradstock, K. F., Bandall, L., Pascovici, D. S., Thomas, M., Erber, W., Huang, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+human+leukaemias+and+lymphomas+using+extensive+immunophenotypes+from+an+antibody+microarray.">Analysis of human leukaemias and lymphomas using extensive immunophenotypes from an antibody microarray.</a> Br. J. Haematol. 135, 184 (2006).</li><li>Belov, L., Huang, P., Barber, N., Mulligan, S. P., Christopherson, R. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Identification+of+repertories+of+surface+antigens+on+leukemias+using+an+antibody+microarray.">Identification of repertories of surface antigens on leukemias using an antibody microarray.</a> Proteomics. 3, 2147 (2003).</li><li>Zhou, J., Belov, L., Huang, P. Y., Shin, J., Solomon, M. J., Chapuis, P. H., Bokey, L., Chan, C., Clarke, C., Clarke, S. J., Christopherson, R. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Surface+antigen+profiling+of+colorectal+cancer+using+antibody+microarrays+with+fluorescence+multiplexing.">Surface antigen profiling of colorectal cancer using antibody microarrays with fluorescence multiplexing.</a> J. Immunol. Methods. 355 (1-2), 40-51 (2010).</li><li>Ellmark, P., Belov, L., Huang, P., Lee, C. S., Solomon, M. J., Morgan, D. K., Christopherson, R. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiplex+detection+of+surface+molecules+on+colorectal+cancers.">Multiplex detection of surface molecules on colorectal cancers.</a> Proteomics. 6, 1791 (2006).</li><li>Pearson, J. P., Allen, A., Hutton, D. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rheology+of+mucin.">Rheology of mucin.</a> Methods Mol. Biol. 125, 99 (2000).</li><li>Yang, Y. H., Dudoit, S., Luu, P., Lin, D. M., Peng, V., Ngai, J., Speed, T. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Normalization+for+cDNA+microarray+data:+a+robust+composite+method+addressing+single+and+multiple+slide+systematic+variation.">Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation.</a> Nucleic Acids Res. 30, 15 (2002).</li><li>Al Saeed, ., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=TMA:+A+free,+open-source+system+for+microarray+data+management+and+analysis.">TMA: A free, open-source system for microarray data management and analysis.</a> BioTechniques. 34, 374-378 (2003).</li></ol>

Nessun conflitto di interessi dichiarati.

In questo video ci dimostra come il microarray anticorpi DotScan può essere utilizzato in modo semplice, semi-quantitativa modo per studiare i profili antigene di superficie per le popolazioni di cellule dal tessuto CRC. Ottenere una sospensione vitale singola cellula da tessuto è fondamentale per il successo dell&#39;esperimento, perché l&#39;energia-dipendente dei processi (ad esempio, l&#39;antigene tappatura e / o formazione di pseudopodi) sembrano essere necessari per il legame ditta...

The author's email has been corrected in the publication of <a href="http://www.jove.com/video/3322">Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing</a>. There was an error with the author, Jerry Zhou's, email. The author's email has been updated to:
j.zhou@uws.edu.au
from:
jzho7551@mail.usyd.edu.au

Erratum: Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing

<table border="1"><tbody><tr><th> Nome del reagente o attrezzature </th><th> Azienda </th><th> Numero di catalogo </th><th> Commenti </th></tr><tr><td> Sale Hanks &#39;soluzione equilibrata </td><td> Sigma-Aldrich </td><td> H6136-10X1L </td><td> Tamponata con 25 mM Hepes (Sigma # H3375) </td></tr><tr><td> Airpure gabinetto di sicurezza biologica di classe II </td><td> Westinghouse </td><td> 1687-2340/612 </td><td></td></tr><tr><td> Lame chirurgiche </td><td> Livingstone </td><td> 090609 </td><td> Confezione da 100 </td></tr><tr><td> RPMI 1640 con 2 mM Hepes </td><td> Sigma-Aldrich </td><td> R4130-10X1L </td><td></td></tr><tr><td> Collagenasi tipo 4 </td><td> Worthington </td><td> 4188 </td><td></td></tr><tr><td> Deossiribonucleasi 1 </td><td> Sigma-Aldrich </td><td> DN25-1G </td><td></td></tr><tr><td> Siringa Terumo (10 ml) </td><td> Terumo </td><td> SS 10 L </td><td> Scatola da 100 </td></tr><tr><td> Filcon Filtro (200 micron) </td><td> BD Biosciences </td><td> 340615 </td><td></td></tr><tr><td> Filcon filtro (50 micron) </td><td> Filcon filtro (50 micron) </td><td> Filcon filtro (50 micron) Filcon filtro (50 micron) 340603 </td><td></td></tr><tr><td> Siero di vitello fetale </td><td> Gibco / Invitrogen </td><td> 10099-141 </td><td></td></tr><tr><td> Centrifuga 5810 R </td><td> Eppendorf </td><td> 7017 </td><td></td></tr><tr><td> Dimetilsolfossido </td><td> Sigma-Aldrich </td><td> D2650 </td><td></td></tr><tr><td> Blu tripano </td><td> Sigma-Aldrich </td><td> T8154 </td><td></td></tr><tr><td> Hemocymeter Technocolor Neubar </td><td> Hirschmann </td><td> non disponibile </td><td></td></tr><tr><td> Microscopio ottico </td><td> Nikon </td><td> Nikon TMS </td><td></td></tr><tr><td> Tubi Cyrovial </td><td> Greiner Bio-One </td><td> 121278 </td><td></td></tr><tr><td> Cryo congelamento contrainer </td><td> Nalgene </td><td> 5100-0001 </td><td></td></tr><tr><td> DotScan anticorpi microarray kit </td><td> Medsaic </td><td> non disponibile </td><td></td></tr><tr><td> DotScan microarray lavare vassoio </td><td> Medsaic </td><td> non disponibile </td><td></td></tr><tr><td> Kimwipes </td><td> Kimberly-Clark </td><td> 4103 </td><td></td></tr><tr><td> Formaldeide 37% </td><td> Sigma-Aldrich </td><td> F1635-500ML </td><td></td></tr><tr><td> DotReaderTM </td><td> Medsaic </td><td> non disponibile </td><td></td></tr><tr><td> Albumina di siero bovino </td><td> Sigma-Aldrich </td><td> A9418-10G </td><td></td></tr><tr><td> Inattivati ​​al calore siero AB 2% </td><td> Invitrogen </td><td> 34005100 </td><td></td></tr><tr><td> Ficoeritrina coniugati CD3 </td><td> Beckman Coulter </td><td> ET386 </td><td></td></tr><tr><td> AlexaFluor647 coniugato EpCAM </td><td> BioLegend </td><td> 324212 </td><td></td></tr><tr><td> Typhoon FLA 9000 </td><td> GE Healthcare </td><td> 28-9558-08 </td><td> Laser 532 nm, 580 BP30 emissione filtro per PE. 633 e 670 nm laser BP30 emissione filtro per Alexa647 </td></tr><tr><td> MultiExperiment Viewer v4.4 </td><td> TM4 Microarray Software Suite </td><td> Software open - source (Rif. 11) </td><td></td></tr></tbody></table>

colorectal cancer cell surface protein profiling using an antibody microarray and fluorescence multiplexing

La prognosi attuale e classificazione dei CRC si basa sulla messa in scena di sistemi che integrano i risultati istopatologici e clinici. Tuttavia, nella maggior parte dei casi CRC, la disfunzione delle cellule è il risultato di numerose mutazioni che modificano l&#39;espressione di proteine ​​e modificazioni post-traduzionali 1. Un certo numero di antigeni di superficie cellulare, tra cui cluster di differenziazione (CD) antigeni, sono stati identificati come potenziali o biomarker prognostico nel CRC metastatico. Questi antigeni rendono ideale come biomarcatori spesso la loro espressione cambia con la progressione del tumore o interazioni con altri tipi di cellule, come i linfociti infiltranti il ​​tumore (TILS) e macrofagi associati al tumore (TAM). L&#39;uso di immunoistochimica (IHC) per il tumore sub-classificazione e la prognosi è ben consolidata per alcuni tipi di tumore 2,3. Tuttavia, nessun singolo &#39;marker&#39; ha mostrato un significato prognostico maggiore clinico-patologici di sosta o guadagnato un largo consenso per l&#39;uso in routine patologia segnalazione di tutti i casi CRC. Un approccio più recente stratificazione prognostica dei fenotipi malattia si basa su profili di proteina di superficie utilizzando più &#39;marker&#39;. Mentre profili di espressione dei tumori con tecniche di proteomica, come iTRAQ è un potente strumento per la scoperta di biomarkers4, non è ottimale per l&#39;uso di routine nei laboratori diagnostici e non può distinguere i diversi tipi di cellule in una popolazione mista. Inoltre, grandi quantità di tessuto tumorale sono necessari per il profiling delle glicoproteine ​​membrana plasmatica purificati da questi metodi. In questo video abbiamo descritto un metodo semplice per la profilatura proteoma superficie delle cellule vitali da disaggregati campioni CRC utilizzando un anticorpo DotScan CRC microarray. Il 122-anticorpo microarray è costituito da un normale 82-anticorpi regione riconoscere una serie di marcatori lignaggio leucociti-specifici, molecole di adesione, recettori e marcatori di infiammazione e la risposta immunitaria 5, insieme ad una regione satellitare per l&#39;individuazione di 40 potenziali marcatori prognostici per la CRC . Le cellule vengono catturati solo gli anticorpi per i quali essi esprimono l&#39;antigene corrispondente. La densità delle cellule per punto, determinato attraverso la scansione ottica, riflette la proporzione di cellule che esprimono l&#39;antigene, il livello di espressione dell&#39;antigene e l&#39;affinità degli anticorpi 6. Per il tessuto CRC o normale mucosa intestinale, scansioni ottiche riflettono l&#39;immunofenotipo delle popolazioni miste di cellule. Multiplexing fluorescenza può quindi essere utilizzato per il profilo selezionato sotto-popolazioni di cellule di interesse catturato l&#39;array. Per esempio, Alexa 647-anti-molecola di adesione delle cellule epiteliali (carcinomi, CD326), è un pan-antigene epiteliale di differenziazione che è stato utilizzato per rilevare le cellule CRC e anche le cellule epiteliali della mucosa intestinale normale, mentre ficoeritrina-anti-CD3, è stato utilizzato per rilevare infiltrazione delle cellule T 7. Il DotScan CRC microarray dovrebbe essere il prototipo di una diagnosi alternativa al anatomicamente basato su sistema di stadiazione CRC.

Watch this Scientific Journal Video about Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing at JoVE.com

Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing

Abbiamo descritto una procedura per la disaggregazione del tumore del colon-retto (CRC) per la produzione di singole cellule vitali, che vengono poi catturate su microarray anticorpi personalizzato riconoscere gli antigeni di superficie (DotScan CRC microarray). Sotto-popolazioni di cellule legato al microarray può essere profilato con multiplazione a fluorescenza utilizzando anticorpi monoclonali taggati con coloranti fluorescenti.

Carcinoma del colon-retto Profilo delle proteine ​​di superficie L&#39;utilizzo di un anticorpo Microarray e Multiplexing fluorescenza

The current prognosis and classification of CRC relies on staging systems that integrate histopathologic and clinical findings. However, in the majority ...

colorectal-cancer-cell-surface-protein-profiling-using-an-antibody

Research

JoVE Journal

Immunology and Infection

13.9K Views.  University of Sydney. Abbiamo descritto una procedura per la disaggregazione del tumore del colon-retto (CRC) per la produzione di singole cellule vitali, che vengono poi catturate su microarray anticorpi personalizzato riconoscere gli antigeni di superficie (DotScan CRC microarray). Sotto-popolazioni di cellule legato al microarray può essere profilato con multiplazione a fluorescenza utilizzando anticorpi monoclonali taggati con coloranti fluorescenti.

Video: Colorectal Cancer Cell Surface Protein Profiling Using an Antibody Microarray and Fluorescence Multiplexing

Using a Pan-Viral Microarray Assay (Virochip) to Screen Clinical Samples for Viral Pathogens

The diagnosis of viral causes of many infectious diseases is difficult due to the inherent sequence diversity of viruses as well as the ongoing emergence of novel viral pathogens, such as SARS coronavirus and 2009 pandemic H1N1 influenza virus, that are not detectable by traditional methods. To address these challenges, we have previously developed and validated a pan-viral microarray platform called the Virochip with the capacity to detect all known viruses as well as novel variants on the basis of conserved sequence homology1. Using the Virochip, we have identified the full spectrum of viruses associated with respiratory infections, including cases of unexplained critical illness in hospitalized patients, with a sensitivity equivalent to or superior to conventional clinical testing2-5. The Virochip has also been used to identify novel viruses, including the SARS coronavirus6,7, a novel rhinovirus clade5, XMRV (a retrovirus linked to prostate cancer)8, avian bornavirus (the cause of a wasting disease in parrots)9, and a novel cardiovirus in children with respiratory and diarrheal illness10. The current version of the Virochip has been ported to an Agilent microarray platform and consists of ~36,000 probes derived from over ~1,500 viruses in GenBank as of December of 2009. Here we demonstrate the steps involved in processing a Virochip assay from start to finish (~24 hour turnaround time), including sample nucleic acid extraction, PCR amplification using random primers, fluorescent dye incorporation, and microarray hybridization, scanning, and analysis.

Using a Pan-Viral Microarray Assay Virochip to Screen Clinical Samples for Viral Pathogens

The Virochip is a pan-viral microarray designed to simultaneously detect all known viruses as well as novel viruses on the basis of conserved sequence homology. Here we demonstrate how to run a Virochip assay to analyze clinical samples for the presence of both known and unknown viruses.

Utilizzando un pan-virale Assay Microarray (Virochip) allo schermo campioni clinici di patogeni virali

The diagnosis of viral causes of many infectious diseases is difficult due to the inherent sequence diversity of viruses as well as the ongoing emergence ...

Ricerca

Immunologia e infezioni

Immuno-fluorescence Assay of Leptospiral Surface-exposed Proteins

Bacterial surface proteins are involved in direct contact with host cells and in uptake of nutrients from the environment 1. For this reason, cellular localization can provide insights into the functional role of bacterial proteins. Surface localization of bacterial proteins is a key step towards identification of virulence factors involved in mechanisms of pathogenicity. 
Methods for fractionating leptospiral membranes 2-5 may be selective for a certain class of outer-membrane proteins (OMPs), such as lipoproteins vs. transmembrane OMPs, and therefore lead to misclassification. This likely is due to structural differences and how they are associated to the outer membrane. Lipoproteins are associated with membranes via a hydrophobic interaction between the N-terminal lipid moiety (three fatty acids) and the lipid bilayer phospholipids 6, 7. In contrast, transmembrane OMPs are typically integrated into the lipid bilayer by amphipathic &beta;-sheets arranged in a barrel-like structure 8, 9. In addition, presence of a protein in the outer-membrane does not necessarily guarantee that the protein or its domains are exposed on the surface. Spirochetal outer membranes are known to be fragile and therefore necessitate methods involving gentle manipulation of cells and inclusion of sub-surface protein controls to assess the integrity of the outer membrane.
Here, we present an immunofluorescence assay (IFA) method to directly assess surface exposure of proteins on intact leptospires. This method is based on recognition of leptospiral surface proteins by antigen-specific antibodies. Herein, antibodies specific for OmpL5410 are detetcted aftero binding to native, surface exposed epitopes. Comparison of antibody reactivity to intact versus permeabilized cells enables evaluation of cellular distribution and whether or not a protein is selectively present on leptospiral surface. The integrity of outer membrane should be assessed using antibody to one or more subsurface proteins, preferably located in the periplasm.
The surface IFA method can be used to analyze surface exposure of any leptospiral protein to which specific antibodies are available. Both the usefulness and limitation of the method depends on whether the antibodies employed are able to bind to native epitopes. Since antibodies often are raised against recombinant proteins, epitopes of native, surface-exposed proteins may not be recognized. Nevertheless, the surface IFA method is a valuable tool for studying components of intact bacterial surfaces. This method can be applied not only for leptospires but also other spirochetes and gram-negative bacteria. For stronger conclusions regarding surface-exposure of OMPs, a comprehensive approach involving several cell localization methods is recommended 10.

An efficient method to assess surface-exposure of leptospiral proteins is described. The method is specifically designed to avoid disruption of the fragile outer membrane of leptospiral cells. This technique requires employment of several negative controls to assess the integrity of the outer membrane and specificity of antibody reaction.

Immuno-fluorescenza saggio di Leptospiral superficie esposti Proteine

Bacterial surface proteins are involved in direct contact with host cells and in uptake of nutrients from the environment 1. For this reason, cellular ...

Single-cell Analysis of Bacillus subtilis Biofilms Using Fluorescence Microscopy and Flow Cytometry

Biofilm formation is a general attribute to almost all bacteria 1-6. When bacteria form biofilms, cells are encased in extracellular matrix that is mostly constituted by proteins and exopolysaccharides, among other factors 7-10. The microbial community encased within the biofilm often shows the differentiation of distinct subpopulation of specialized cells 11-17. These subpopulations coexist and often show spatial and temporal organization within the biofilm 18-21.
Biofilm formation in the model organism Bacillus subtilis requires the differentiation of distinct subpopulations of specialized cells. Among them, the subpopulation of matrix producers, responsible to produce and secrete the extracellular matrix of the biofilm is essential for biofilm formation 11,19. Hence, differentiation of matrix producers is a hallmark of biofilm formation in B. subtilis.
We have used fluorescent reporters to visualize and quantify the subpopulation of matrix producers in biofilms of B. subtilis 15,19,22-24. Concretely, we have observed that the subpopulation of matrix producers differentiates in response to the presence of self-produced extracellular signal surfactin 25. Interestingly, surfactin is produced by a subpopulation of specialized cells different from the subpopulation of matrix producers 15.
We have detailed in this report the technical approach necessary to visualize and quantify the subpopulation of matrix producers and surfactin producers within the biofilms of B. subtilis. To do this, fluorescent reporters of genes required for matrix production and surfactin production are inserted into the chromosome of B. subtilis. Reporters are expressed only in a subpopulation of specialized cells. Then, the subpopulations can be monitored using fluorescence microscopy and flow cytometry (See Fig 1).
The fact that different subpopulations of specialized cells coexist within multicellular communities of bacteria gives us a different perspective about the regulation of gene expression in prokaryotes. This protocol addresses this phenomenon experimentally and it can be easily adapted to any other working model, to elucidate the molecular mechanisms underlying phenotypic heterogeneity within a microbial community.

Single-cell Analysis of Bacillus subtilis Biofilms Using Fluorescence Microscopy and Flow Cytometry

Microbial biofilms are generally constituted by distinct subpopulations of specialized cells. Single-cell analysis of these subpopulations requires the use of fluorescent reporters. Here we describe a protocol to visualize and monitor several subpopulationswithin B. subtilis biofilms using fluorescence microscopy and flow cytometry.

Singola cella Analisi Bacillus subtilis I biofilm usando la microscopia a fluorescenza e citometria a flusso

Biofilm formation is a general attribute to almost all bacteria 1-6. When bacteria form biofilms, cells are encased in extracellular matrix that is mostly ...

Visualization of Bacterial Toxin Induced Responses Using Live Cell Fluorescence Microscopy

Bacterial toxins bind to cholesterol in membranes, forming pores that allow for leakage of cellular contents and influx of materials from the external environment. The cell can either recover from this insult, which requires active membrane repair processes, or else die depending on the amount of toxin exposure and cell type1. In addition, these toxins induce strong inflammatory responses in infected hosts through activation of immune cells, including macrophages, which produce an array of pro-inflammatory cytokines2. Many Gram positive bacteria produce cholesterol binding toxins which have been shown to contribute to their virulence through largely uncharacterized mechanisms.
Morphologic changes in the plasma membrane of cells exposed to these toxins include their sequestration into cholesterol-enriched surface protrusions, which can be shed into the extracellular space, suggesting an intrinsic cellular defense mechanism3,4. This process occurs on all cells in the absence of metabolic activity, and can be visualized using EM after chemical fixation4. In immune cells such as macrophages that mediate inflammation in response to toxin exposure, induced membrane vesicles are suggested to contain cytokines of the IL-1 family and may be responsible both for shedding toxin and disseminating these pro-inflammatory cytokines5,6,7. A link between IL-1&beta; release and a specific type of cell death, termed pyroptosis has been suggested, as both are caspase-1 dependent processes8. To sort out the complexities of this macrophage response, which includes toxin binding, shedding of membrane vesicles, cytokine release, and potentially cell death, we have developed labeling techniques and fluorescence microscopy methods that allow for real time visualization of toxin-cell interactions, including measurements of dysfunction and death (Figure 1). Use of live cell imaging is necessary due to limitations in other techniques. Biochemical approaches cannot resolve effects occurring in individual cells, while flow cytometry does not offer high resolution, real-time visualization of individual cells. The methods described here can be applied to kinetic analysis of responses induced by other stimuli involving complex phenotypic changes in cells.

Methods for purifying the cholesterol binding toxin streptolysin O from recombinant E. coli and visualization of toxin binding to live eukaryotic cells are described. Localized delivery of toxin induces rapid and complex changes in targeted cells revealing novel aspects of toxin biology.

Visualizzazione delle risposte tossina batterica provocata con diretta microscopia a fluorescenza cellulare

Bacterial toxins bind to cholesterol in membranes, forming pores that allow for leakage of cellular contents and influx of materials from the external ...

A Comparative Approach to Characterize the Landscape of Host-Pathogen Protein-Protein Interactions

Significant efforts were gathered to generate large-scale comprehensive protein-protein interaction network maps. This is instrumental to understand the pathogen-host relationships and was essentially performed by genetic screenings in yeast two-hybrid systems. The recent improvement of protein-protein interaction detection by a Gaussia luciferase-based fragment complementation assay now offers the opportunity to develop integrative comparative interactomic approaches necessary to rigorously compare interaction profiles of proteins from different pathogen strain variants against a common set of cellular factors.
This paper specifically focuses on the utility of combining two orthogonal methods to generate protein-protein interaction datasets: yeast two-hybrid (Y2H) and a new assay, high-throughput Gaussia princeps protein complementation assay (HT-GPCA) performed in mammalian cells.
A large-scale identification of cellular partners of a pathogen protein is performed by mating-based yeast two-hybrid screenings of cDNA libraries using multiple pathogen strain variants. A subset of interacting partners selected on a high-confidence statistical scoring is further validated in mammalian cells for pair-wise interactions with the whole set of pathogen variants proteins using HT-GPCA. This combination of two complementary methods improves the robustness of the interaction dataset, and allows the performance of a stringent comparative interaction analysis. Such comparative interactomics constitute a reliable and powerful strategy to decipher any pathogen-host interplays.

This article focuses on the identification of high-confident interaction datasets between host and pathogen proteins using a combination of two orthogonal methods: yeast two-hybrid followed by a high-throughput interaction assay in mammalian cells called HT-GPCA.

Un approccio comparato alla caratterizzano il paesaggio di ospite-patogeno interazioni proteina-proteina

Significant efforts were gathered to generate  large-scale comprehensive protein-protein interaction network maps. This is  instrumental to understand the ...

A Miniaturized Glycan Microarray Assay for Assessing Avidity and Specificity of Influenza A Virus Hemagglutinins

Influenza A virus (IAV) hemagglutinins recognize sialic acids on the cell surface as functional receptors to gain entry into cells. Wild waterfowl are the natural reservoir for IAV, but IAV can cross the species barrier to poultry, swine, horses and humans. Avian viruses recognize sialic acid attached to a penultimate galactose by a &#945;2-3 linkage (avian-type receptors) whereas human viruses preferentially recognize sialic acid with a &#945;2-6 linkage (human-type receptors). To monitor if avian viruses are adapting to human type receptors, several methods can be used. Glycan microarrays with diverse libraries of synthetic sialosides are increasingly used to evaluate receptor specificity. However, this technique is not used for measuring avidities. Measurement of avidity is typically achieved by evaluating the binding of serially diluted hemagglutinin or virus to glycans adsorbed to conventional polypropylene 96-well plates. In this assay, glycans with &#945;2-3 or &#945;2-6 sialic acids are coupled to biotin and adsorbed to streptavidin plates, or are coupled to polyacrylamide (PAA) which directly adsorb to the plastic. We have significantly miniaturized this assay by directly printing PAA-linked sialosides and their non PAA-linked counterparts on micro-well glass slides. This set-up, with 48 arrays on a single slide, enables simultaneous assays of 6 glycan binding proteins at 8 dilutions, interrogating 6 different glycans, including two non-sialylated controls. This is equivalent to 18x 96-well plates in the traditional plate assay. The glycan array format decreases consumption of compounds and biologicals and thus greatly enhances efficiency.

Using a printed glycan microarray strategy, a conventional 96-well plate assay was miniaturized for analysis of influenza A virus hemagglutinin avidity and specificity for sialic acid containing receptors.

Un miniaturizzato Glycan microarray test per la valutazione avidità e Specificità del virus influenzale A emoagglutinine

Influenza A virus (IAV) hemagglutinins recognize sialic acids on the cell surface as functional receptors to gain entry into cells. Wild waterfowl are the ...

Antibody Labeling with Fluorescent Dyes Using Magnetic Protein A and Protein G Beads

Antibodies labeled with small molecules like fluorescent dyes, cytotoxic drugs, and radioactive tracers are essential tools in biomedical research, immunodiagnostics and more recently as therapeutic agents. Traditional methods for labeling antibodies with small molecules require purified antibodies at relatively high concentration, involve multiple dialysis steps and have limited throughput. However, several applications, including the field of Antibody Drug Conjugates (ADCs), will benefit from new methods that will allow labeling of antibodies directly from cell media. Such methods may allow antibodies to be screened in biologically relevant assays, for example, the receptor-mediated antibody internalization assay in the case of ADCs. Here, we describe a method (on-bead method) that enables labeling of small amounts of antibodies directly from cell media. This approach utilizes high capacity magnetic Protein A and Protein G affinity beads to capture antibodies from the cell media followed by labeling with small molecules using either amine or thiol chemistry and subsequent elution of the labeled antibodies. Taking fluorescent dyes as surrogates for small molecules, we demonstrate the on-bead labeling of three different mouse antibodies directly from cell media using both amine and thiol labeling chemistry. The high binding affinity of antibodies to Protein A and Protein G ensures high recoveries as well as high purity of the labeled antibodies. In addition, use of magnetic beads allows multiple samples to be handled manually, thereby significantly improving labeling throughput.

The on-bead method for labeling antibodies with small molecules enables labeling of a small amount of antibodies directly from cell media. This method is compatible with amine and thiol chemistry, and can handle multiple samples in parallel, manually or using automated platforms.

Anticorpo etichettatura con coloranti fluorescenti utilizzando proteine ​​magnetica A e proteine ​​G perline

Antibodies labeled with small molecules like fluorescent dyes, cytotoxic drugs, and radioactive tracers are essential tools in biomedical research, ...

A Protein Microarray Assay for Serological Determination of Antigen-specific Antibody Responses Following Clostridium difficile Infection

We provide a detailed overview of a novel high-throughput protein microarray assay for the determination of anti-Clostridium difficile antibody levels in human sera and in separate preparations of polyclonal intravenous immunoglobulin (IVIg). The protocol describes the methodological steps involved in sample preparation, printing of arrays, assay procedure, and data analysis. In addition, this protocol could be further developed to incorporate diverse clinical samples including plasma and cell culture supernatants. We show how protein microarray can be used to determine a combination of isotype (IgG, IgA, IgM), subclass (IgG1, IgG2, IgG3, IgG4, IgA1, IgA2), and strain-specific antibodies to highly purified whole C. difficile toxins A and B (toxinotype 0, strain VPI 10463, ribotype 087), toxin B from a C. difficile toxin-B-only expressing strain (CCUG 20309), a precursor form of a B fragment of binary toxin, pCDTb, ribotype-specific whole surface layer proteins (SLPs; 001, 002, 027), and control proteins (tetanus toxoid and Candida albicans). During the experiment, microarrays are probed with sera from individuals with C. difficile infection (CDI), individuals with cystic fibrosis (CF) without diarrhea, healthy controls (HC), and from individuals pre- and post-IVIg therapy for the treatment of CDI, combined immunodeficiency disorder, and chronic inflammatory demyelinating polyradiculopathy. We encounter significant differences in toxin neutralization efficacies and multi-isotype specific antibody levels between patient groups, commercial preparations of IVIg, and sera before and following IVIg administration. Also, there is a significant correlation between microarray and enzyme-linked immunosorbent assay (ELISA) for antitoxin IgG levels in serum samples. These results suggest that microarray could become a promising tool for profiling antibody responses to C.difficile antigens in vaccinated or infected humans. With further refinement of antigen panels and a reduction in production costs, we anticipate that microarray technology may help optimize and select the most clinically useful immunotherapies for C. difficile infection in a patient-specific manner.

A Protein Microarray Assay for Serological Determination of Antigen-specific Antibody Responses Following Clostridium difficile Infection

This article describes a simple protein microarray method for profiling humoral immune responses to a 7-plex panel of highly purified Clostridium difficile antigens in human sera. The protocol can be extended for the determination of specific antibody responses in preparations of polyclonal intravenous immunoglobulin.

Un'analisi di Microarray della proteina per determinazione sierologica dell'infezione di Clostridium difficile anticorpo seguenti risposte antigene-specifiche

We provide a detailed overview of a novel high-throughput protein microarray assay for the determination of anti-Clostridium difficile antibody levels in ...

Single-cell Quantitation of mRNA and Surface Protein Expression in Simian Immunodeficiency Virus-infected CD4+ T Cells Isolated from Rhesus macaques

Single-cell analysis is an important tool for dissecting heterogeneous populations of cells. The identification and isolation of rare cells can be difficult. To overcome this challenge, a methodology combining indexed flow cytometry and high-throughput multiplexed quantitative polymerase chain reaction (qPCR) was developed. The objective was to identify and characterize simian immunodeficiency virus (SIV)-infected cells present within rhesus macaques. Through quantitation of surface protein by fluorescence-activated cell sorting (FACS) and mRNA by qPCR, virus-infected cells are identified by viral gene expression, which is combined with host gene and protein measurements to create a multidimensional profile. We term the approach, targeted Single-Cell Proteo-transcriptional Evaluation, or tSCEPTRE. To perform the method, viable cells are stained with fluorescent antibodies specific for surface markers used for FACS isolation of a cell subset and/or downstream phenotypic analysis. Single cells are sorted followed by immediate lysis, multiplex reverse transcription (RT), PCR pre-amplification, and high throughput qPCR of up to 96 transcripts. FACS measurements are recorded at the time of sorting and subsequently linked to the gene expression data by well position to create a combined protein and transcriptional profile. To study SIV-infected cells directly ex vivo, cells were identified by qPCR detection of multiple viral RNA species. The combination of viral transcripts and the quantity of each provide a framework for classifying cells into distinct stages of the viral life cycle (e.g., productive versus non-productive). Moreover, tSCEPTRE of SIV+ cells were compared to uninfected cells isolated from the same specimen to assess differentially expressed host genes and proteins. The analysis revealed previously unappreciated viral RNA expression heterogeneity among infected cells as well as in vivo SIV-mediated post-transcriptional gene regulation with single-cell resolution. The tSCEPTRE method is relevant for the analysis of any cell population amenable to identification by expression of surface protein marker(s), host or pathogen gene(s), or combinations thereof.

Single-cell Quantitation of mRNA and Surface Protein Expression in Simian Immunodeficiency Virus-infected CD4+ T Cells Isolated from Rhesus macaques

Described is a methodology to quantitate the expression of 96 genes and 18 surface proteins by single cells ex vivo, allowing for the identification of differentially expressed genes and proteins in virus-infected cells relative to uninfected cells. We apply the approach to study SIV-infected CD4+ T cells isolated from rhesus macaques.

Cella singola quantificazione del mRNA e l'espressione di proteine di superficie CD4 infettati da Virus di immunodeficienza delle scimmie+ T cellule isolate da macachi Rhesus

Single-cell analysis is an important tool for dissecting heterogeneous populations of cells. The identification and isolation of rare cells can be ...

Using Enhanced Green Fluorescence Protein-expressing Escherichia Coli to Assess Mouse Peritoneal Macrophage Phagocytosis

This manuscript describes a simple and reproducible method to perform a phagocytosis assay. The first part of this method involves building a pET-SUMO-EGFP vector (SUMO = small ubiquitin-like modifier) and expressing enhanced green fluorescence protein (EGFP) in Escherichia coli (BL21DE). EGFP-expressing E. coli is coincubated with macrophages for 1 h at 37 &#176;C; the negative control group is incubated on ice for the same amount of time. Then, the macrophages are ready for assessment. The advantages of this technique include its simple and straightforward steps, and phagocytosis can be measured by both flow cytometer and fluorescence microscope. The EGFP-expressing E. coli are stable and display a strong fluorescence signal even after the macrophages are fixed with paraformaldehyde. This method is not only suitable for the assessment of macrophage cell lines or primary macrophages in vitro but also suitable for the evaluation of granulocyte and monocyte phagocytosis in peripheral blood mononuclear cells. The results show that the phagocytic capability of peritoneal macrophages from young (eight-week-old) mice is higher than that of macrophages from aged (16-month-old) mice. In summary, this method measures macrophage phagocytosis and is suitable for studying the innate immune system function.

Using Enhanced Green Fluorescence Protein-expressing Escherichia Coli to Assess Mouse Peritoneal Macrophage Phagocytosis

Here, we present a protocol to assess mouse peritoneal macrophage phagocytosis using enhanced green fluorescence protein-expressing Escherichia coli.

Utilizzando Enhanced fluorescenza verde che esprimono proteine Escherichia Coli per valutare la fagocitosi dei macrofagi peritoneali del Mouse

Carcinoma del colon-retto Profilo delle proteine ​​di superficie L'utilizzo di un anticorpo Microarray e Multiplexing fluorescenza

Carcinoma del colon-retto Profilo delle proteine di superficie L'utilizzo di un anticorpo Microarray e Multiplexing fluorescenza